A Low Energy and Adaptive Architecture for Efficient Routing and Robust Mobility Management in Wireless Sensor Networks

Wireless sensor networks are composed of low cost and extremely power constrained sensor nodes which are scattered over a region forming multi-hop and self organized networks, making energy consumption a crucial design issue. These networks are used for various applications such as field monitoring, home automation, seismic and medical data collection or surveillance. Research has shown that clustering sensor nodes is an efficient method to manage energy consumption for prolonging the network lifetime. In this paper we propose a new architecture called HARP, a \emph{Hierarchical Adaptive and Reliable Routing Protocol}, a clustering algorithm which builds inter-cluster and intra-cluster hierarchical trees, which are optimized to save power. This architecture is scalable and can be used in both homogeneous and heterogeneous wireless sensor networks. By means of the addition of a \emph{recovery slot} in the scheduling scheme, HARP provides efficient link fault tolerance and also supports node mobility management. The same process can additionally function as a joining mechanism for newly deployed nodes. This architecture is highly adaptive to specific application requirements and provides bounded-time data transmissions. Furthermore, a new cluster head election formulation and its associated data gathering protocol (s-HARP) is proposed. This protocol optimizes and balances the energy consumption in the network. Our performance evaluation has shown that HARP and s-HARP can significantly reduce the energy consumption and prolong the useful lifetime of the network in typical applications as compared with the most popular wireless sensor network protocol.